Digital Commons Network^™

Comparing Poor And Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy In Acute Ischemic Stroke, Matthias A. Mutke, Vince I. Madai, Adam Hilbert, Esra Zihni, Arne Potreck, Charlotte S. Weyland, Markus A. Mohlenbruch, Sabine Heiland, Peter A. Ringleb, Simon Nagel, Martin Beendszus, Dietmar Frey

Articles

Outcome prediction after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) is commonly performed by focusing on favorable outcome (modified Rankin Scale, mRS 0–2) after 3 months but poor outcome representing severe disability and mortality (mRS 5 and 6) might be of equal importance for clinical decision-making.

Corrigendum: Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P. A. Hancock

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In the published article, the name of Gabriella Hancock was incorrectly written as “Gabriela M. Hancock.” The correct name is “Gabriella Hancock.” In the published article, there was also an error in the author list as published. Gabriella Hancock was listed as the last author, but should have been listed as third author. P. A. Hancock was listed as third author but should be listed as the last author. The corrected author list appears below. Luca Longo1, Christopher D.Wickens, Gabriella Hancock and P. A. Hancock. The authors apologize for this error and state that this does not change the scientific …

Detection Of Grape Clusters In Images Using Convolutional Neural Network, Mohammad Osama Shahzad, Anas Bin Aqeel, Waqar Shahid Qureshi

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Convolutional Neural Networks and Deep Learning have revolutionized every field since their inception. Agriculture has also been reaping the fruits of developments in mentioned fields. Technology is being revolutionized to increase yield, save water wastage, take care of diseased weeds, and also increase the profit of farmers. Grapes are among the highest profit-yielding and important fruit related to the juice industry. Pakistan being an agricultural country, can widely benefit by cultivating and improving grapes per hectare yield. The biggest challenge in harvesting grapes to date is to detect their cluster successfully; many approaches tend to answer this problem by harvest …

How Visual Stimuli Evoked P300 Is Transforming The Brain–Computer Interface Landscape: A Prisma Compliant Systematic Review, Jai Kalra, Prashasti Mittal, Nirmiti Mittal, Abhishek Arora, Utkarsh Tewari, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Luca Longo

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Non-invasive Visual Stimuli evoked-EEGbased P300 BCIs have gained immense attention in recent years due to their ability to help patients with disability using BCI-controlled assistive devices and applications. In addition to the medical field, P300 BCI has applications in entertainment, robotics, and education. The current article systematically reviews 147 articles that were published between 2006-2021*. Articles that pass the pre-defined criteria are included in the study. Further, classification based on their primary focus, including article orientation, participants’ age groups, tasks given, databases, the EEG devices used in the studies, classification models, and application domain, is performed. The application-based classification considers …

An Aggregation-Based Algebraic Multigrid Method With Deflation Techniques And Modified Generic Factored Approximate Sparse Inverses, Anastasia Natsiou, George A. Gravvanis, Christos K. Filelis-Papadopoulos, Konstantinos M. Giannoutakis

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In this paper, we examine deflation-based algebraic multigrid methods for solving large systems of linear equations. Aggregation of the unknown terms is applied for coarsening, while deflation techniques are proposed for improving the rate of convergence. More specifically, the V-cycle strategy is adopted, in which, at each iteration, the solution is computed by initially decomposing it utilizing two complementary subspaces. The approximate solution is formed by combining the solution obtained using multigrids and deflation. In order to improve performance and convergence behavior, the proposed scheme was coupled with the Modified Generic Factored Approximate Sparse Inverse preconditioner. Furthermore, a parallel version …

Nesnet: A Deep Network For Estimating Near-Surface Pollutant Concentrations, Prasanjit Dey, Bibhash Pran Das, Yee Hui Lee, Soumyabrata Dev

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Atmospheric pollution has become a serious threat in recent years. The advancements and expansion of industrial activity and civilization have been the major catalysts. With serious consequences like climate change and global warming, the onset of which is already being observed, keeping a check on atmospheric pollutant levels is now more important than ever. Trace gases play a major role in atmospheric chemistry. Many of these are also regarded as major atmospheric pollutants. The concentration of gases, such as (SO2), (O3), (NO2), etc., are indicators of air quality. Therefore, in this study, we primarily concern ourselves with concentrations of NO2, …

Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha

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In this paper, we meta-analyse the empirical evidence about the effectiveness of game-based interventions to reduce students' level of math anxiety. After performing a search for randomised controlled studies relevant to game-based intervention for math anxiety, 16 experimental studies with a total of 686 participants described in 11 peer-review articles met the selection criteria.A random-effects meta-analysis indicated a small and non-significant reduction of math anxiety (mean effect size ES=-0.32, CI=[-0.64,0.01]). The results were moderated by several factors: non-digital games were more effective, while digital games had a negligible mean effect size of $ES=-0.13$, $CI=[-0.33,0.08]$. The effect size was moderated also …

Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand

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Rapid growth in the utilization of the inverter-interfaced distributed energy resources (IIDERs) in microgrids has brought new challenges in the network protection area. Microgrid protection specifically becomes a concern during operation in the islanded mode. There is a considerable reduction in fault current levels in this mode compared to when the microgrid is connected to the grid, which makes conventional algorithms operate with significant delay or, in many cases, not even pick up the fault. This paper proposes a protection algorithm based on the rate of change of direct-axis current component ( id ) to protect inverter-based microgrids (IBMGs). The …

Opportunities Of Iot In Fog Computing For High Fault Tolerance And Sustainable Energy Optimization, A. Reyana, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

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Today, the importance of enhanced quality of service and energy optimization has promoted research into sensor applications such as pervasive health monitoring, distributed computing, etc. In general, the resulting sensor data are stored on the cloud server for future processing. For this purpose, recently, the use of fog computing from a real-world perspective has emerged, utilizing end-user nodes and neighboring edge devices to perform computation and communication. This paper aims to develop a quality-of-service-based energy optimization (QoS-EO) scheme for the wireless sensor environments deployed in fog computing. The fog nodes deployed in specific geographical areas cover the sensor activity performed …

A Multidimensionality Reduction Approach To Rainfall Prediction, Menatallah Abdel Azeem, Prasanjit Dey, Soumyabrata Dev

Articles

The rainfall has an impact on various fields and industries, including transportation, construction, tourism, health, and wildlife preservation. Accurate rainfall prediction is essential for mitigating the negative impact of rainfall on these sectors. However, previous studies on rainfall prediction have been mainly based on datasets from North America, Europe, Australia, and Central Asia, covering different periods. This study proposes using weather datasets covering the past 5 to 10 years to capture recent patterns in weather data. Additionally, the curse of dimensionality can impact model performance and lead to overfitting. Therefore, this study proposes utilizing dimensionality reduction techniques to ensure that …

An Integrated Model For Information Adoption&Trust In Mobile Social Commerce, Fulya Acikgoz, Abdelsalam Busalim, James Gaskin, Shahla Asadi

Articles

ABSTRACT Despite the growing importance of mobile social commerce (ms-commerce), little research has been conducted on the effects of informational and social factors on users’ post-adoption behavior. We, therefore, build on the understanding of mobile social commerce in the UK market and how it affects users’ post-adoption behaviors. Our theoretical model leverages the information adoption model, social support theory, and social influence theory. Data was gathered from 377 ms-commerce users from the UK and analyzed via Partial Least Squares (PLS-SEM). The research findings show that both informational and social factors have a positive impact on information adoption in ms-commerce apps. …

A Multi–Objective Gaining–Sharing Knowledge-Based Optimization Algorithm For Solving Engineering Problems, Nour Elhouda Chalabi, Abdelouahab Attia, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Hatem Masri, Ali Wagdy Mohamed

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Metaheuristics in recent years has proven its effectiveness; however, robust algorithms that can solve real-world problems are always needed. In this paper, we suggest the first extended version of the recently introduced gaining–sharing knowledge optimization (GSK) algorithm, named multiobjective gaining–sharing knowledge optimization (MOGSK), to deal with multiobjective optimization problems (MOPs). MOGSK employs an external archive population to store the nondominated solutions generated thus far, with the aim of guiding the solutions during the exploration process. Furthermore, fast nondominated sorting with crowding distance was incorporated to sustain the diversity of the solutions and ensure the convergence towards the Pareto optimal set, …

Assessing The Impact Of Contact Tracing With An Agent-Based Model For Simulating The Spread Of Covid-19: The Irish Experience, Elizabeth Hunter, Sudipta Saha, Jwenish Kumawat, Ciara Carroll, John Kelleher, Claire Buckley, Conor Mcaloon, Patricia Kearney, Michelle Gilbert, Greg Martin

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Contact tracing is an important tool in managing infectious disease outbreaks and Ireland used a comprehensive contact tracing program to slow the spread of COVID-19. Although the benefits of contact tracing seem obvious, it is difficult to estimate the actual impact contact tracing has on an outbreak because it is hard to separate the effects of contact tracing from other behavioural changes or interventions. To understand the impact contact tracing had in Ireland, we used an agent-based model that is designed to simulate the spread of COVID-19 through Ireland. The model uses real contact tracing data from the first year …

Interpreting Disentangled Representations Of Person-Specific Convolutional Variational Autoencoders Of Spatially Preserving Eeg Topographic Maps Via Clustering And Visual Plausibility, Taufique Ahmed, Luca Longo

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Dimensionality reduction and producing simple representations of electroencephalography (EEG) signals are challenging problems. Variational autoencoders (VAEs) have been employed for EEG data creation, augmentation, and automatic feature extraction. In most of the studies, VAE latent space interpretation is used to detect only the out-of-order distribution latent variable for anomaly detection. However, the interpretation and visualisation of all latent space components disclose information about how the model arrives at its conclusion. The main contribution of this study is interpreting the disentangled representation of VAE by activating only one latent component at a time, whereas the values for the remaining components are …

The Potential And Limitations Of Conversational Agents For Chronic Conditions And Well-Being, Ekaterina Uetova, Lucy Hederman, Robert J. Ross, Dympna O'Sullivan

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Conversational agents are becoming more common in the health and wellness domains in part due to assumptions regarding potential improvements in individuals’ outcomes. This paper presents initial findings from a review of conversational agent use in healthcare for chronic conditions and well-being. A search of the literature was performed on electronic databases PubMed, ACM Digital Library, Scopus and IEEE Xplore. Studies were included if they were focused on chronic disorder management, disease prevention or lifestyle change and if systems were tested on target user groups. This paper investigates the health domains, the user profiles and reasons why conversational agents may …

Developing Persuasive Systems For Marketing: The Interplay Of Persuasion Techniques, Customer Traits And Persuasive Message Design, Annye Braca, Pierpaolo Dondio

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This paper presents a comprehensive review of persuasion techniques and their applications in the context of designing persuasive communication systems for marketing purposes. The study provides a condensed taxonomy of techniques and offers examples to guide the development of effective persuasive messages. Furthermore, the paper explores how attitudes, personality traits, and emotions can be leveraged as input data in predictive models, including machine learning approaches. The study's findings offer valuable insights for the design and implementation of persuasive communication systems across diverse contexts, including marketing and advertising, public health campaigns, and political messaging. This paper has the potential to serve …

Supporting Clinical Decision Making In The Emergency Department For Paediatric Patients Using Machine Learning: A Scoping Review Protocol, Fiona Leonard, Dympna O. Sullivan, John Gilligan, Nicola O. Shea, Michael J. Barrett

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Introduction Machine learning as a clinical decision support system tool has the potential to assist clinicians who must make complex and accurate medical decisions in fast paced environments such as the emergency department. This paper presents a protocol for a scoping review, with the objective of summarising the existing research on machine learning clinical decision support system tools in the emergency department, focusing on models that can be used for paediatric patients, where a knowledge gap exists. Materials and methods The methodology used will follow the scoping study framework of Arksey and O'Malley, along with other guidelines. Machine learning clinical …

Considerations For Scaling A Social Enterprise: Key Factors And Elements, Clodagh O'Reilly, Lucia Walsh, Ziene Mottiar

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No abstract provided.

Systematic Review Of Clinical Practice Guidelines For Uveitis, Nima Ghadiri, Ian R. Reekie, Iris Gordon, Sare Safi, Gareth Lingham, Jennifer R. Evans, Stuart Keel

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To facilitate the integration of eye care into universal health coverage, the WHO is developing a Package of Eye Care Interventions (PECI). Development of the PECI involves the identification of evidence-based interventions from relevant clinical practice guidelines (CPGs) for uveitis.

A systematic review of CPGs published on uveitis between 2010 and March 2020 was conducted. CPGs passing title and abstract and full-text screening were evaluated using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool and data on recommended interventions extracted using a standard data extraction sheet.

Blockchain Games And A Disruptive Corporate Business Model, Xuan-Thao Nguyen

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This Article is the first to identify and theorize on a new disruptive corporate business model unfolding in the gaming industry that is larger than both the movie and music sectors combined. Corporations in blockchain gaming reject the old paradigm of amassing profits by turning the public into spenders for and consumers of corporate products. The new corporate business model transforms members of the public into producers and true owners of new corporate property while earning income and garnering governance voting rights. Through a case study of Axie Infinity, a blockchain game launched in 2021, this Article explores how the …

How Has Entrepreneurship Opportunity Formation Amongst Immigrants Been Influenced By The Covid-19 Pandemic?, Osa-Godwin Osaghae, Thomas M. Cooney

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The purpose of this paper is to investigate how entrepreneurship opportunity formation amongst immigrants has been influenced by the COVID-19 pandemic, given that environmental changes and irregularity can contribute to entrepreneurship opportunity formation in the immigrant set-up.

Beyond Competing For Talent: An Integrative Framework For Coopetition In Talent Management In Smes, Stefan Jooss, Julia Lenz, Ralf Burbach

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This paper aims to unpack how small and medium-sized enterprises (SMEs) can operationalise coopetition in talent management, addressing ongoing talent shortages in the hospitality industry which were intensified during the Covid-19 pandemic

Overview Of Various Components Of Lateral-Flow Immunochromatography Assay For The Monitoring Of Aflatoxin And Limit Of Detection In Food Products: A Systematic Review, Thasmin Shahjahan, Bilal Javed, Vinayak Sharma, Furong Tian

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The detection of aflatoxins is essential for the food industry to ensure the safety and quality of food products before their release to the market. The lateral-flow immunochromatography assay (LFIA) is a simple technique that allows the rapid on-site detection of aflatoxins. The purpose of this review is to evaluate and compare the limits of detection reported in the most recent research articles, published between the years of 2015 and 2023. The limits of detection (LODs) were compared against the particle type and particle size, as well as other variables, to identify trends and correlations among the parameters. A growing …

Surface-Modified Silver Nanoparticles And Their Encapsulation In Liposomes Can Treat Mcf-7 Breast Cancer Cells, Ellenor Moors, Vinayak Sharma, Furong Tian, Bilal Javed

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Silver nanoparticles (AgNPs) have emerged as a promising tool for cancer treatment due to their unique physicochemical and biological properties. However, their clinical applications are limited by their potential cytotoxicity caused due to oxidation stress and non-specific cellular uptake pathways. To overcome these barriers, surface modifications of AgNPs have been proposed as an effective strategy to enhance their biocompatibility and specificity toward cancer cells. In this study, AgNPs were synthesised using the chemical reduction method and subsequently conjugated with various capping agents such as Polyvinylpyrrolidone (PVP) and Bovine Serum Albumin (BSA). Further, this study involves the synthesis of liposomes by …

Defamation With Bayesian Audiences, Yonathan A. Arbel, Murat C. Mungan

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How strictly should the law regulate false defamatory statements? We first show that the presence of judicial errors often puts defamation law on a Laffer curve: regulation that is too lax or too strict is inferior to moderate regulation. While moderate regulation is ideal, it is not always attainable because of practical and legal constraints. With these constraints, we consider a Bayesian audience that takes the strictness of defamation law into account when evaluating statements. The optimal standard is then taxer than is prescribed by standard models with naive audiences. These findings underscore the importance of accounting for audience effects …

The Credibility Effect: Defamation Law And Audiences, Yonathan A. Arbel

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What should be the legal response to false statements? In the context of defamation law, courts try to set a standard that balances the interests of speakers and their potential targets. This article empirically demonstrates an unappreciated effect of such decisions on third parties: a credibility effect. Using a series of lab experiments, I find that defamation law makes individuals more trusting of reports from various media. This credibility effect is desirable when the report is true but can lead to unintended consequences in the case of misinformation. In particular, the credibility effect is shown to cast a stigma on …

Policing Protest: Speech, Space, Crime, And The Jury, Jenny E. Carroll

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Speech is more than just an individual right-it can serve as a catalyst for democratically driven revolution and reform, particularly for minority or marginalized positions. In the past decade, the nation has experienced a rise in mass protests. However, dissent and disobedience in the form of such protests is not without consequences. While the First Amendment promises broad rights of speech and assembly, these rights are not absolute. Criminal law regularly curtails such rights - either by directly regulating speech as speech or by imposing incidental burdens on speech as it seeks to promote other state interests. This Feature examines …

The Public Voice Of The Defender,, Russell M. Gold, Kay L. Levine

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For decades, police and prosecutors have controlled the public narrative about criminal law. The news landscape features salacious stories of violent crimes while ignoring the more mundane but far more prevalent minor cases that clog the court dockets. Defenders, faced with overwhelming caseloads and fear that speaking out may harm their clients, have largely ceded the opportunity to offer a counternarrative based on what they see every day. Defenders tell each other about the overuse of pretrial detention, intensive pressure to plead guilty, overzealous prosecutors, cycles of violence, and rampant constitutional violations-all of which inflict severe harm on defendants and …

Associations Between Maternal Metabolic Parameters During Pregnancy And Fetal And Child Growth Trajectories From 20 Weeks' Gestation To 5 Years Of Age: Secondary Analysis From The Rolo Longitudinal Birth Cohort Study, Helena C. Bartels, Linda M. O'Keeffe, Cara A. Yelverton, Kate N. O'Neill, Aisling A. Geraghty, Eileen C. O'Brien, Sarah Louise Killeen, Ciara Mcdonnell, Fionnuala M. Mcauliffe

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Objective: To examine the association between maternal metabolic parameters in pregnancy and growth trajectories up to 5 years of age. Methods: Data from mother–child pairs who participated in the ROLO study, a randomized trial examining the impact of a low glycaemic index diet on the recurrence of macrosomia, were analysed. Fetal and child growth trajectories were developed from longitudinal measurements from 20 weeks gestation up to 5 years of age. We examined associations between maternal fasting glucose, insulin, HOMA-IR and leptin, taken in early pregnancy (14–16 weeks) and late pregnancy (28 weeks), and weight (kg) and abdominal circumference (cm) trajectories …

Do The Culturable Microbial Groups Present In Cutaway Bogs Change According To Temporal Variation? Pilot Study Based On The Midlands In The Republic Of Ireland, Gouri Nilakshika Atapattu, Tara Battersby, Michelle Giltrap, Furong Tian

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Cutaway peatlands in the midlands of the Republic of Ireland are rarely the focus of scientific studies. The soil quality and related microenvironment have been severely impacted by peat extraction. Returning them to a ‘near-natural state' would require greater insights into this ecological niche. The current research took the initiative to study the microbiology of vast cutaway sites in the midlands of Ireland. Peat was collected over two seasons in January, February and April. Homogenised peat was aseptically cultured on a range of specific and non-specific culture media. Microbial enumeration, Gram staining and other microscopic observations of morphologically distinct microorganisms …